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A practical approach to timeseries forecasting using Python.
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Pandas cookbook : recipes for scientific computing, time series analysis and data visualization using Python /
Table of Contents: “…Pandas foundations -- Dissecting the anatomy of a DataFrame -- Accessing the main DataFrame components -- Understanding data types -- Selecting a single column of data as a series -- Calling series methods -- Working with operators on a series -- Chaining series methods together -- Making the index meaningful -- Renaming row and column names -- Creating and deleting columns -- Essential Chapter 2: DataFrame operations -- Selecting multiple DataFrame columns -- Selecting columns with methods -- Ordering column names sensibly -- Operating on the entire DataFrame -- Chaining DataFrame methds together -- Working with operators on a DataFrame -- Comparing missing values -- Transposing the direction of a DataFrame operation -- Determining college campus diversity -- Chapter 3: Beginning data analysis -- Developing a data analysis routine.…”
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Pandas cookbook : recipes for scientific computing, time series analysis and data visualization using Python /
Table of Contents: “…Pandas foundations -- Dissecting the anatomy of a DataFrame -- Accessing the main DataFrame components -- Understanding data types -- Selecting a single column of data as a series -- Calling series methods -- Working with operators on a series -- Chaining series methods together -- Making the index meaningful -- Renaming row and column names -- Creating and deleting columns -- Essential Chapter 2: DataFrame operations -- Selecting multiple DataFrame columns -- Selecting columns with methods -- Ordering column names sensibly -- Operating on the entire DataFrame -- Chaining DataFrame methds together -- Working with operators on a DataFrame -- Comparing missing values -- Transposing the direction of a DataFrame operation -- Determining college campus diversity -- Chapter 3: Beginning data analysis -- Developing a data analysis routine.…”
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Python data analytics : with Pandas, NumPy, and Matplotlib /
Table of Contents: “…A Module Repository for WindowsTesting Your pandas Installation; Getting Started with pandas; Introduction to pandas Data Structures; The Series; Declaring a Series; Selecting the Internal Elements; Assigning Values to the Elements; Defining a Series from NumPy Arrays and Other Series; Filtering Values; Operations and Mathematical Functions; Evaluating Vales; NaN Values; Series as Dictionaries; Operations Between Series; The DataFrame; Defining a Dataframe; Selecting Elements; Assigning Values; Membership of a Value; Deleting a Column; Filtering; DataFrame from Nested dict.…”
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